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ORCID5. MLG 2007: Firenze, Italy
- Paolo Frasconi, Kristian Kersting, Koji Tsuda:
Mining and Learning with Graphs, MLG 2007, Firence, Italy, August 1-3, 2007, Proceedings. 2007
Session 1
- Pierre Baldi:
Learning and Charting Chemical Space with Strings and Graphs: Challenges and Opportunities for AI and Machine Learning. - Mario Boley, Tamás Horváth, Axel Poigné, Stefan Wrobel:
Efficient Closed Pattern Mining in Strongly Accessible Set Systems. - Ulf Brefeld, Thoralf Klein, Tobias Scheffer:
Support Vector Machines for Collective Inference. - Thomas Gärtner, Gemma C. Garriga:
The Cost of Learning Directed Cuts. - Kaspar Riesen, Stefan Fankhauser, Horst Bunke:
Speeding Up Graph Edit Distance Computation with a Bipartite Heuristic.
Session 2
- Luc De Raedt:
ProbLog and its Application to Link Mining in Biological Networks. - Manfred Jaeger, Petr Lidman, Juan L. Mateo:
Comparative Evaluation of PL languages. - Kristiaan Pelckmans, Johan A. K. Suykens:
Transductive Rademacher Complexities for Learning Over a Graph. - Hendrik Blockeel, Tijn Witsenburg, Joost N. Kok:
Graphs, Hypergraphs, and Inductive Logic Programming. - Yana Volkovich, Nelly Litvak, Debora Donato:
Web Graph Parameters and the Pagerank Distribution. - Shankar Vembu, Thomas Gärtner, Stefan Wrobel:
Semidefinite Ranking on Graphs. - Davide Bacciu, Alessio Botta, Dan C. Stefanescu:
Augmenting the Distributed Evaluation of Path Queries on Data-Graphs with Information Granules.
Session 3
- Jiawei Han:
Mining, Indexing, and Searching Graphs in Large Data Sets. - Mathias Fiedler, Christian Borgelt:
Support Computation for Mining Frequent Subgraphs in a Single Graph. - Jan Ramon, Siegfried Nijssen:
General Graph Refinement with Polynomial Delay. - Christian Desrosiers, Philippe Galinier, Pierre Hansen, Alain Hertz:
Improving Frequent Subgraph Mining in the Presence of Symmetry. - Alexandre Termier, Yoshinori Tamada, Kazuyuki Numata, Seiya Imoto, Takashi Washio, Tomoyuki Higuchi:
DIGDAG, a First Algorithm to Mine Closed Frequent Embedded Sub-DAGs.
Session 4
- Lise Getoor:
Graph Identification. - Shawndra Hill, Foster J. Provost, Chris Volinsky:
Learning and Inference in Massive Social Networks. - Jianzhong Chen, Stephen H. Muggleton, Jose Santos:
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning. - Karsten M. Borgwardt, Tobias Petri, S. V. N. Vishwanathan, Hans-Peter Kriegel:
An Efficient Sampling Scheme For Comparison of Large Graphs. - Zhao Xu, Volker Tresp, Shipeng Yu, Kai Yu, Hans-Peter Kriegel:
Fast Inference in Infinite Hidden Relational Models.
Session 5
- Alexander J. Smola:
Learning Graph Matching. - Janne Sinkkonen, Janne Aukia, Samuel Kaski:
Inferring Vertex Properties from Topology in Large Networks. - Leander Schietgat, Jan Ramon, Maurice Bruynooghe:
A Polynomial-time Metric for Outerplanar Graphs. - Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, Gökhan H. Bakir:
Weighted Substructure Mining for Image Analysis. - Thomas Gärtner:
Efficient Kernel Methods for Graphs. - Leonid Kontorovich:
A Universal Kernel for Learning Regular Languages.
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